Stochastic stability of fuzzy Hopfield neural networks with time-varying delays

摘要

It is well known that a complex nonlinear system can be represented as a Takagi-Sugeno(T-S) Fuzzy model that consists of a set of linear sub-models. This letter is concerned with the global asymptotical stability analysis problem for stochastic fuzzy Hopfield neural networks with successive time delay components. By using the stochastic analysis approach, stability criterion is derived in terms of linear matrix inequalities( LMIs), which can be effectively solved by standard software.